Velocity-Based Training From Theory To Application

Velocity-Based Training:
From Theory to
Application
Jonathon Weakley, PhD,1,2 Bryan Mann, PhD,3 Harry Banyard, PhD,4 Shaun McLaren, PhD,2,5 Tannath Scott, PhD,2,6
and Amador Garcia-Ramos, PhD7,8
1
AU1 School of Behavioural and Health Sciences, Australian Campus University, Brisbane, Queensland, Australia;
2
Carnegie Applied Rugby Research (CARR) Centre, Institute for Sport, Physical Activity and Leisure, Leeds Beckett
AU2 University, Leeds, West Yorkshire, United Kingdom; 3Department of Kinesiology and Sport Sciences, University of
Miami, Miami, Florida; 4Department of Health and Medical Sciences, Swinburne University of Technology, Melbourne,
Australia; 5England Performance Unit, The Rugby Football League, Leeds, West Yorkshire, United Kingdom; 6School
of Science and Technology, University of New England, Armidale, Australia; 7Department of Sports Sciences and
Physical Conditioning, Faculty of Education, Universidad Catolica de la Santisima Concepcion, Concepción, Chile;
and 8Department of Physical Education and Sport, Faculty of Sport Sciences, University of Granada, Granada, Spain
Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided
in the HTML and PDF versions of this article on the journal’s Web site (http://journals.lww.com/nsca-scj).
ABSTRACT to an individual’s maximal ability (e.g., integration of VBT lies on a continuum

70% of one repetition maximum and can be used with varying emphasis
Velocity-based training (VBT) is a con-
[1RM]) (35,95). In addition, athletes (Figure 1). At its most basic level, F1
temporary method of resistance training
are commonly assigned a specified num- velocity can be used as an accessory
that enables accurate and objective to traditional percentage-based train-
ber of sets and repetitions to complete
prescription of resistance training inten- ing. For example, visual or verbal feed-
(e.g., 5 sets of 10 repetitions) based on the
sities and volumes. This review provides back of velocity can be provided to
desired training goal (9). However, using
an applied framework for the theory and an athlete’s previous maximal ability to athletes to enhance performance and
application of VBT. Specifically, this prescribe training loads can be problem- improve motivation and competitive-
review gives detail on how to: use atic if the athlete’s 1RM changes as a con- ness (1,90,91,93,96). Alternatively,
velocity to provide objective feedback, sequence of training because the VBT can be implemented across all
estimate strength, develop load-velocity prescribed load may not match the % facets of a resistance training program-
profiles for accurate load prescription, of 1RM intended for the particular ses- ming and support the prescription of
and how to use statistics to monitor sion. In addition, it is known that the load, sets, number of repetitions, and
velocity. Furthermore, a discussion on number of repetitions that can be per- the programming method applied
the use of velocity loss thresholds, dif- formed with a given % of 1RM differs (9,20,49,95). For this reason, VBT
ferent methods of VBT prescription, and between athletes and, therefore, assign- should be defined as a method that
how VBT can be implemented within ing the same number of sets and repeti- “uses velocity to inform or enhance
traditional programming models and mi- tions for all athletes may induce different training practice.” This definition ac-
crocycles is provided. levels of effort and fatigue (72,88). There- counts for the broad implementation
fore, alternative methods such as of training methods that use velocity
velocity-based training (VBT) have been and assist the practitioner in achieving
INTRODUCTION
their training goals.
thletes perform resistance train- developed to provide accurate and
A ing to develop strength, power,

and lean body mass (81,82). To
achieve this, coaches typically prescribe
objective data to support the prescription
of resistance training (7–9).
WHAT IS VELOCITY-BASED
specific resistance training loads relative KEY WORDS:
TRAINING?
VBT; 1RM prediction; load-velocity pro-
Address correspondence to Dr. Jonathon VBT is a term that covers a wide array file; periodization; fatigue; statistics
Weakley, Jonathon.weakley@acu.edu.au. of training topics and approaches. The
2 VOLUME 00 | NUMBER 00 | MONTH 2020 Copyright Ó National Strength and Conditioning Association
Copyright © National Strength and Conditioning Association. Unauthorized reproduction of this article is prohibited.
conscientiousness, verbally encourag-
ing statements after each repetition
may provide the greatest benefit (92).
Finally, the chronic delivery of feed-
back during training is known to be
of substantial benefit. Over a 6-week
period, Randell et al. (71) provided
either feedback or no-feedback at the
Figure 1. Velocity-based training continuum highlighting the varying emphasis on completion of each repetition of the
velocity within a training program. jump squat and observed small to mod-
erately greater improvements in stand-
ing broad jump (effect size [ES] 5
WHY VELOCITY? of feedback can cause improvements in 0.28) and 30 m sprint performance
Velocity is commonly used over other performance in male (96) and female (ES 5 0.46). In addition, recent
kinetic or kinematic outputs (e.g., (93), adults (92) and adolescents research by Weakley et al. (90) has
power) when resistance training for 3 (93,96), and professional (1,59) and highlighted greater improvements in
reasons. First, it is well established that nonprofessional (50) athletes. Not only 10- and 20-m sprint performance (ES
as an external mass is increased, reduc- do these improvements occur instanta- 5 0.69 and 0.71, respectively), jump
tions in lifting velocity occur (45). This neously during training (93,96) but height (ES 5 0.21), and 3RM squat
loss of velocity continues until a 1RM also when feedback is supplied and and bench press strength (ES 5 0.28
load is achieved which corresponds then removed, performance returns and 0.21, respectively) when feedback
with the minimum/terminal velocity to baseline levels (50). These changes is provided after each repetition of each
threshold (V1RM) (45). Second, there in performance have been found to exercise across a 4-week mesocycle.
is a nearly perfect linear relationship occur alongside improvements in Also, of interest for the strength and
between velocity and intensity as a per- psychological characteristics, with conditioning practitioner, was that this
centage of maximum ability (i.e., % of increases in motivation and compet- study emphasized the benefit of pro-
1RM). This has been demonstrated con- itiveness being demonstrated when viding feedback of performance when
sistently across a range of exercises and feedback of velocity performance is performing sprint drills (Table 1). AU5
submaximal loads (13,27). Third, a com- provided (92,93,96–98). Sprint times and average velocity T1
mon element to many definitions of across a known distance can easily be
Although feedback of velocity can eas-
exercise-induced fatigue is that as fatigue conveyed to athletes and are believed
ily be provided within the training rou-
increases, there is a transient decline in to promote similar improvements in
tine, the frequency, method of delivery,
muscle fiber shortening speeds, relaxa- motivation and feelings of competitive-
and personality of the athlete should
tion times, and force-generating capac- ness within and between athletes as
be considered. Recent research (59)
ity that cause subsequent reductions in feedback during resistance train-
has demonstrated that different modes
voluntary exercise velocity (33,74). Put ing (90).
of feedback delivery influence perfor-
simply, as fatigue accrues, exercise veloc- mance adaptations. Nagata et al. (59)
ity decreases. By acknowledging these THE DIFFERENT TYPE OF
has shown immediate improvements VELOCITY VARIABLES AND WHEN
fundamental concepts, practitioners and greater long-term physical devel- TO USE THEM
can use velocity outputs to accurately opment of loaded jump ability when The 2 velocity variables most com-
and objectively prescribe external loads verbal feedback of barbell velocity is monly used in practice and scientific
and training volumes for each session,
supplied after each repetition. This research are mean velocity (MV) (i.e.,
irrespective of fluctuations in fatigue and
was compared with the provision of the average velocity across the entire
athlete readiness.
average set velocity or a visual record- concentric phase) and peak velocity
USING VELOCITY TO PROVIDE ing of the set. Furthermore, it is (PV) (i.e., the maximum instantaneous
FEEDBACK AND ENHANCE acknowledged that athletes may have velocity reached during the concentric
PERFORMANCE a preference of whether they are visu- phase) (68,83). However, mean propul-
The use of feedback during resistance ally or verbally informed of their per- sive velocity (MPV) (i.e., the average
training is a powerful tool for acute performance outcomes (92). These velocity from the start of the concen-
formance enhancement and adaptation. differences may be due to intrinsic or tric phase until the acceleration is less
Although feedback can occur in many extrinsic motivating factors (i.e., com- than gravity [29.81 m$s22]) has also
forms, visual and verbal feedback of bar- petition within or between athletes) been proposed as an alternative (77).
bell velocities have received the most and levels of athlete conscientiousness The difference between the MPV and
investigation (1,50,59,92,93,96,98). It (92). However, it should be noted that MV is that the latter does not account
has been demonstrated that these forms in athletes with low levels of for the braking phase of the movement.
3
Strength and Conditioning Journal | www.nsca-scj.com
Applying Velocity-Based Training
Table 1
Feedback variables and their effects on acute-training performance
Variable
Frequency Frequency after each repetition has been shown to have greater effects than after each set
(59)
Quantitative vs. qualitative Quantitative feedback of velocity enhances performance greater than observing video
recording of previous exercise (59).
Conscientiousness Athletes with low levels of conscientiousness have the greatest improvements in kinematic
outputs when verbal encouragement is supplied (92).
Motivation and competitiveness When visual feedback of kinematic outputs are supplied, improvements are observed in both
males and females (92,93,96–98)
Intrinsically vs. extrinsically Intrinsically motivated athletes may prefer visual feedback, while extrinsically motivated may
motivated athletes prefer to hear feedback (92).
Encouragement Verbally encouraging statements can enhance barbell velocity and power output (92).
However, it is our opinion that MV and On the other hand, nonballistic var- ONE REPETITION MAXIMUM
PV provide more valuable information iants of exercises are advised for testing PREDICTION METHODS
for strength and conditioning practi- heavier loads (.70% 1RM), with MV One interesting application of VBT is
tioners for both testing and training and MPV providing virtually the same the possibility of estimating 1RM
purposes. information (28,32,76). Therefore, strength from the velocity recorded
when testing “heavy” (.70% 1RM), against submaximal loads. General
MONITORING VELOCITY DURING nonballistic exercises, all velocity vari- load-velocity (L-V) relationships (36)
TESTING ables could be equally valid. and individual L-V relationships (52)
Neuromuscular function can be as- have previously been proposed to
sessed by measuring the velocity value estimate the 1RM. The general L-V rela-
achieved against a given load using tra- MONITORING VELOCITY DURING tionship was introduced by González-
ditional (e.g., bench press or squat) or TRAINING Badillo and Sánchez-Medina (36) who AU6
ballistic (e.g., bench press throw or ver- Although velocity can be used in many used a second-order polynomial regres-
tical jump) exercises (15,66). When ways during training, 3 important ap- sion equation to estimate the %1RM dur-
testing with light/moderate loads plications are (I) estimating the 1RM, ing the bench press exercise. After this
(#70% 1RM), it is recommended that (II) prescribing the volume and relative seminal work, similar equations have
ballistic exercises are used (e.g., bench intensity of the training session based been proposed in other resistance train-
press throw rather than the traditional off the magnitude of velocity loss, and ing exercises (3,5,13,28,30,31,54,65,75).
bench press variant). This removes the (III) increasing motivation and com- Although general L-V relationship equa-
braking portion of the concentric petitiveness through the provision of tions enable a quick estimation of the
movement and can provide greater real-time velocity feedback. Presum- 1RM from the MVrecorded during a sin-
reliability of velocity outcomes ably, all 3 velocity variables could be gle repetition, coaches should be aware
(61,66). However, using MV and equally valid to fulfill the applications of several limitations that may limit their
MPV to measure ballistic performance of points II and III. However, we rec- use in practice. Briefly, the relationship
is problematic because these metrics ommend the use of MV to estimate the between the MV recorded during a single
include the flight phase. Furthermore, 1RM because of its greater reliability repetition and the %1RM may be influ-
MPV values could be even more prob- (when compared with MPV) when enced by the type of exercise (e.g., squat
lematic due to difficulties in detecting lifting light relative loads (23,67). The versus leg press) (13,38,75), execution
the exact moment take-off occurs. This advantage of MV over PV is that the technique (e.g., concentric-only vs.
issue may explain counterintuitive find- former varies less between different de- eccentric-concentric) (28,65), sex (higher
ings reported in the scientific literature vices designed to measure movement values for men at lower %1RM) (3,84),
such as the power developed in a tradi- velocity (22,30), the relationship and measurement device (4,22,26,91). Of
tional exercise (e.g., bench press) being between load and velocity is more lin- even more importance could be that the
greater than its ballistic variant (e.g., ear using MV (31), and that between- MV-%1RM relationship, especially at
bench press throw) (46). Conse- subject variability in the velocity at- light relative loads, is subject-specific
quently, we recommend the use of tained during 1RM attempts may (70). Finally, from a statistical point of
PV for the testing of ballistic exercises. be lower. view, another problem of the general
4 VOLUME 00 | NUMBER 00 | MONTH 2020
L-V relationships is an overestimation of associated with individualized L-V pro- compared with using a general V1RM.
the data fit because of the presence of filing is the selection of the V1RM used However, this assumption needs to be
autocorrelation because authors included to predict the 1RM. Previous studies supported with experimental data. To
more than one observation from the have used the individual V1RM (6,73) date, no study has compared the preci-
same participant to calculate the general or mean V1RM for all subjects (24). sion in the estimation of the 1RM when
L-V relationships (60). However, because of the low reliability using the individual and general V1RM.
The individual L-V relationship was pro- of the individual V1RM (6,29,73), and
Since the individual L-V relationship is
posed to overcome the limitations high- the trivial differences between the
highly linear (6,47,73), a solution to
lighted above. The standard test used to between- and within-subject variability
for the V1RM (70), the use of a general reduce the duration of the testing pro-
determine the individual L-V relation- cedure could be to determine the indi-
V1RM for all subjects could be recom-
ship consists of recording MV against vidual L-V relationship from the MV
mended to simplify the testing proce-
multiple submaximal loads (z5 loads) dure. The V1RM reported in the recorded against only 2 loads (i.e., 2-
and, subsequently, modeling the L-V scientific literature for commonly used point method) (24,25). This has been
relationship through a linear regression resistance training exercises is provided demonstrated by Garcı́a-Ramos et al.
to estimate the 1RM as the load associ- in Table 2. It is also possible that using (24) who have shown that the individual
ated with the MV of the 1RM (V1RM) the individual V1RM would provide L-V relationship modeled through the 2-
T2 (6,73) (Table 2). The biggest challenge a more accurate estimation of the 1RM point method provides a more accurate
Table 2
Minimum velocity threshold for commonly used resistance training exercises
Exercise Study Sample 1RM MV (mean 6 SD) V1RM

Bench press González-Badillo and Sánchez-Medinaa (32) 120 young healthy males 0.16 6 0.04 m/s 0.17 m/s
Sánchez-Medinaa et al. (75) 75 athletes 0.17 6 0.04 m/s
Garcı́a-Ramosa et al. (27) 30 healthy males 0.17 6 0.03 m/s
Helms et al. (38) 15 powerlifters 0.10 6 0.04 m/s
Prone bench Loturco et al. (54) 30 athletes 0.51 6 0.07 m/s 0.50 m/s
pull Sánchez-Medinaa et al. (75) 75 athletes 0.52 6 0.06 m/s
Garcı́a-Ramos et al. (30) 26 athletes 0.48 6 0.04 m/s
Prone pull-up Sánchez-Moreno et al. (78) 52 firefighter candidates 0.20 6 0.05 m/s 0.23 m/s
Muñoz-Lopez et al. (58) 82 resistance-trained males 0.26 6 0.05 m/s
Seated military Balsalobre-Fernándeza et al. (3) 39 resistance trained 0.19 6 0.05 m/s 0.19 m/s
press Garcı́a-Ramosa et al. (29) participants 0.20 6 0.05 m/s
24 healthy participants
Lat pulldown Perez-Castilla et al. (69) 23 healthy participants 0.47 6 0.04 m/s 0.47 m/s
Seated cable row Perez-Castilla et al. (69) 23 healthy participants 0.40 6 0.05 m/s 0.40 m/s
Squat a
Conceição et al. (13) 15 male athletes 0.32 6 0.04 m/s 0.30 m/s
Sánchez-Medina anda González-Badillo 80 strength-trained males 0.32 6 0.03 m/s
(74) 17 strength-trained males 0.24 6 0.06 m/s
Banyard et al. (6) 15 powerlifters 0.23 6 0.05 m/s
Helms et al. (38)
Deadlift Ruf et al. (73) 11 resistance-trained athletes Not stated 0.15 m/s
Helms et al. (38) 15 powerlifters 0.14 6 0.05 m/s
Lake et al. (50) 12 active males 0.16 6 0.05 m/s
Hip-thrust de Hoyo et al. (20) 102 sport science students 0.25 6 0.03 m/s 0.25 m/s
Leg press Conceição et al. (13) 15 male athletes 0.21 6 0.04 m/s 0.21 m/s
a
Smith machine variation of the exercise.
1RM 5 one repetition maximum; MV 5 mean velocity; V1RM 5 velocity at 1RM.
5
estimation of the bench press 1RM per- accuracy of the 2-point method and across training sessions and legitimate
formed in a Smith machine than previ- other velocity-based 1RM prediction fluctuations in velocity that occur from
ously published general L-V methods is expected to be compromised training-induced adaptation. This is crit-
relationships. Furthermore, provided during free-weight lower-body exercises ical, so that decisions regarding training
that 2 distant loads are used (e.g., (6,43,44,52). Therefore, although the load modification can be made with
approximately 45% 1RM and 85% recommendations provided in this sec- a high degree of accuracy. Recent stud-
1RM), the addition of intermediate tion can be followed to obtain an accu- ies have shown that the L-V relationship
loads does not significantly improve rate estimation of the 1RM during some is stable when using MV, PV, or MPV in
the precision in the estimation of the upper-body exercises, it should be noted the free-weight back squat and Smith
1RM (69). The validity of the 2-point that the available scientific evidence in- machine bench press (8,27). In terms of
method has also been confirmed for dicates that velocity recordings cannot meaningful changes in velocity, the
upper-body free-weight exercises (e.g., be used to obtain an accurate estimation smallest detectable difference in MV,
bench pull (31) and bench press (48)) of the 1RM during lower-body exercises PV, and MPV for the free-weight back
and also during the lat pull-down and such as the squat or deadlift. It is squat has been reported to be 60.06–
seated cable row exercises (69), but its hypothesized that discrepancies in the
0.08 m$s21, 60.11–0.19 m$s21, and
validity has never been explored during accuracy of prediction may be due to
60.08–0.11 m$s21, respectively (6). This
lower-body exercises. Therefore, the greater technical complexity of
suggests that if valid velocity measuring
coaches are encouraged to use the 2- lower-body exercises (e.g., squat or
devices are used for monitoring, mean-
point method as an accurate, quick, deadlift) compared with upper-body ex-
ingful changes in velocity between train-
and relatively fatigue-free method to ercises (e.g., bench press or bench pull).
ing sessions are likely to reflect acute
estimate the 1RM during upper-body Finally, it should also be noted that the
exercises. This can be performed in 3 direct measurement of the 1RM is more fatigue or gains in strength. Furthermore,
simple steps: (I) setting of the exercise- reliable than the estimation from the L- it may also allow for the accurate pre-
specific V1RM (found within Table 2), V relationship (24). scription of resistance training load dur-
(II) recording of the MV against a light ing training and across mesocycles.
(z45% 1RM) and a heavy load (z85% DEVELOPING A LOAD-VELOCITY There are 4 simple steps for the devel-
1RM), and (III) modelling of the indi- PROFILE FOR THE PRESCRIPTION opment of an individualized L-V profile
vidual load-velocity relationship and OF MEAN SET VELOCITIES (Table 3) (8). First, the athlete performs T3
determining the 1RM as the load asso- A key aspect of training with L-V pro- a 1RM assessment in the relevant exer-
ciated with the V1RM. However, files is for a coach to differentiate cise to determine their maximum
coaches should be aware that the between normal variation in velocity strength and to allow for monitoring
Table 3
Steps for developing an L-V profile for an athlete in the back squat
Session 1 Session 2
1. Warm-up with dynamic movements and stretches 1. After 48-h rest, the athlete returns and completes repetitions
with 20, 40, 60, 80, and 90% of 1RM
2. Complete 3 repetitions at 20, 40, and 60%. 2. Three repetitions should be used for loads 20–60% and 1
repetition for 80–90%.
3. Complete 1 repetition at 80 and 90%. 3. For sets that involved multiple repetitions (i.e., loads 20–60%),
the repetition with the fastest MV should be recorded.
4. Then 5 maximal attempts at achieving a 1RM are permitted# 4. With this information, individualized L-V profiles can be
constructed within Microsoft Excel using the MV plotted
against relative load and by applying a line of best fit.
5. After successful attempts, barbell load can be increased in 5. A linear regression equation can then be used to modify
consultation with the athlete with loads between 0.5 and 2.5 training loads within and between sessions
kg.
6. The last successful attempt with a full depth squat with
correct technique can be established as the 1RM.
48 hours have been provided between testing occasions.
1RM 5 one repetition maximum.
of velocity against %1RM over time. a “snapshot” of an athlete’s fitness- a “normal” range of performance,
Second (if completing a 1RM assess- fatigue status. For example, when lift- should the test be hypothetically
ment provide at least 24 hours’ recov- ing a fixed external load, changes in repeated over and over (Figure 3). F3
ery), perform an incremental loading peak or mean concentric velocities When assessing changes in perfor-
test. Previous research has used either may be indicative of altered neuromus- mance, the SE can be used to create
method 1: 3 repetitions with 20, 40, cular qualities (91). Reductions in an individual confidence interval (CI)
and 60%, and one repetition with 80 velocity may be symptomatic of around change scores and represent
and 90% 1RM, with sets performed 2 mi- fatigue, overreaching/overtraining, or uncertainty in an observed perfor-
nutes apart (8,9) or method 2: the “2- detraining/maladaptation, whereas mance change (i.e., accounting for
point method” with repetitions per- faster velocities could signify improve- the “noise”). This provides the practi-
formed at 2 approximate loads of ments in neuromuscular capacity or tioner a plausible range of values that
;45% 1RM and ;85% 1RM (24). In acute potentiation (17). are compatible with the data assump-
step 3, the velocity data of the fastest When interpreting an athlete’s velocity- tions (34) (Figure 4, see Appendix 2, F4
repetition from each intensity based testing data, coaches must con- Supplemental Digital Content 2,
F2 (Figure 2A) are plotted against the cor- sider both the reliability of test perfor- http://links.lww.com/SCJ/A278).
responding relative load (%1RM), and mance, as well as the practical
then, a linear line of best fit is applied To know how practically important
importance of a change. The reliability a change might be, coaches must decide
to extrapolate the regression equation of test performance is influenced by
(Figure 2B). The final step is to create on a threshold for a decisive change
measurement error (which is a funda- and evaluate changes against this value.
a velocity table from the regression mental consideration when purchasing
equation. This table uses the MV of Importantly, this concept is entirely
velocity tracking equipment) and nor- separate from the previously discussed
the training set, corresponds with a per- mal variation within the body’s biolog-
centage of maximum, and can be imple- issues of performance reliability, noise,
ical systems. A useful metric to quantify and uncertainty. In a hypothetical
mented in much the same way a coach performance reliability is the within-
would traditionally prescribe from a rel- world where performance is entirely
athlete standard (typical) error (SE). stable and changes only due to system-
ative load (%RM) table (refer to Helms This can be estimated from a group-
T4 et al. (37)). In the example table (Table 4) atic effects (i.e., fitness or fatigue),
based test-retest reliability study (2,39) changes could simply be evaluated
if this athlete wanted to complete 6 rep- or from the trend in an athlete’s individ-
etitions at a “Heavy” intensity, the mean against a threshold that represents
ual test performance repeated across some value representing practical sig-
set velocity should be approximately a theoretically stable period (e.g., days,
0.58 m$s21. This information may be nificance. In this regard, we recom-
weeks, months) (36,41) (see Appendix mend using an anchor-based
particularly useful for practitioners when 1, Supplemental Digital Content 1,
accounting for differing rates in adapta- approach (79), whereby changes can
http://links.lww.com/SCJ/A277). be evaluated against a value represent-
tion and for the adjustment of training
loads within and across training sessions. The SE is reflective of the “typical” ing a “real-world” difference in perfor-
variation in an athlete’s performance mance. For example, an increase of
METHODS TO INTERPRET (e.g., mean concentric velocity) that one-third of the competition-to-
CHANGES IN VELOCITY-BASED are due to random factors causing nat- competition variability in solo athlete
DATA ural fluctuation. Therefore, applying performance, such as weight lifted, best
Velocity-based testing can serve as the SE to observed test scores as a 6 time, distance thrown, etc., results in
a useful tool for coaches to gain value can be used to represent one extra medal every 10 competitions
Figure 2. (A) Mean velocity data attained from an athlete’s L-V profile during the barbell back squat; (B) data, linear regression, and
equation for this athlete’s L-V profile.
7
Table 4 expert coach opinion or existing

An example of an individualized mean set velocity table for the free-weight research on the associations between
back squat with each mean set velocity corresponding to a prescribed test and competitive performance.
number of repetitions and intensity range Other approaches, such as
distribution-based (e.g., smallest
Mean velocity table (m$s21) worthwhile effect), are available, but
Repetitions can produce arbitrary values lacking
real-world relevance (14).
Intensity 1 2 3 4 5 6 7 8 9 10
Once a threshold of practical impor-
Maximum 0.26 0.34 0.38 0.41 0.47 0.51 0.54 0.57 0.60 0.63 tance has been established, coaches
Very heavy 0.29 0.35 0.39 0.42 0.48 0.52 0.55 0.58 0.61 0.64 can combine the previously mentioned
concepts and make a decision on an
Heavy 0.35 0.42 0.46 0.49 0.54 0.58 0.61 0.64 0.67 0.69
athlete’s velocity-based testing data.
Moderately heavy 0.42 0.49 0.53 0.55 0.60 0.64 0.67 0.70 0.72 0.75 Of course, we do not operate in a world
Moderate 0.50 0.56 0.59 0.62 0.67 0.70 0.73 0.75 0.78 0.80 where performance is entirely stable,
Moderately light 0.57 0.63 0.66 0.68 0.73 0.76 0.79 0.81 0.83 0.86 and therefore, coaches must also con-
Light 0.64 0.70 0.73 0.75 0.79 0.83 0.85 0.87 0.89 0.91 sider performance uncertainty. A very
simple and effective way of achieving
Very light 0.71 0.76 0.80 0.82 0.86 0.89 0.91 0.93 0.95 0.97
this is to visualize the performance
change with its CI against the region
(40). This is often a practice intuitive to experience of what changes really
of practical importance (16) (Figure 3).
expert coaches who set performance make a difference. This threshold infor-
The decision process is informed by
targets based on their knowledge and mation could therefore be derived from
interpreting the amount of overlap
between the CI and the decisive
threshold. Two such methods that
can assist this include the second-
generation p-value (SGPV) (10,11)
and tests of equivalence using 2 one-
sided tests (TOST) (52,53). In particu-
lar, the SGPV is intended as a descrip-
tive statistic (10) and may therefore be
useful when applied to monitoring
changes in an athlete’s velocity-based
performance. It is beyond the scope of
our review to discuss the application of
SGPV and TOST in detail (refer to
Blume et al. (10,11), Lakens (52) and
Lakens et al. (53)), but we provide sev-
eral recommendations for coaches
using the aforementioned principles
to interpret velocity-based testing data
(see Appendix 3, Supplemental Digital
Content 3, http://links.lww.com/
SCJ/A279). An analysis of changes in
a powerlifter’s mean concentric veloc-
Figure 3. Mean concentric velocity (MCV) from 100-kg warm-up sets of the barbell
ity from 100-kg warm-up sets of the
back squat throughout a powerlifter’s 17-week training phase. Data are
shown as the fastest performance achieved each week 6 the standard barbell back squat throughout a 7-
(typical) error, derived from the maintenance phase trend (i.e., baseline; week training phase (Figure 3) using
straight red line, weeks 1–10; see Appendix 2, Supplemental Digital Con- several of the concepts we have dis-
tent 2, http://links.lww.com/SCJ/A278). Loading phase changes from cussed is displayed in Figure 5. F5
baseline are evaluated at an alpha of 0.20 (i.e., 80% confidence level). Gray
shaded area 5 trivial, based on a minimum practically important difference MANAGEMENT OF FATIGUE
of 6 0.03 m$s21 and the maintenance trend standard error. From the USING RELATIVE VELOCITY LOSS
athletes’ known load-velocity profile, a 0.03-m$s21 change in mean con- THRESHOLDS
centric velocity is indicative of a ;1% change in 1 repetition maximum, It is common knowledge that humans
which is 0.3 3 the competition-to-competition variability of 3.1%. come in different shapes and sizes and
that occur when relative velocity loss
thresholds are applied and allows for
individualization during each set and at
each load/velocity (89). This diverges
from percentage-based methods that
promotes the strength coach to set
arbitrary repetition and set schemes
(e.g., 4 sets of 10 repetitions) that do
not account for athlete differences,
Figure 4. Hypothetical example of confidence intervals (CIs) applied to a change in daily readiness, or within-session
mean concentric velocity. Data are shown as the change 6 CI, scaled fatigue accrual.
against a minimum practically important difference of 6 0.03 m$s21 (gray Perhaps more important than the con-
area).
trol over training session kinetic and
kinematic outputs is the improved abil-
individuals have different physical and ensure improved prescription and to ity to dictate internal and subsequent
physiological capacities (e.g., marathon mitigate divergency in fatigue and adap- fatigue outcomes by using velocity loss
runners compared to sprinters). How- tive responses, relative velocity loss thresholds (Figure 6). Recent work F6
ever, strength and conditioning practi- thresholds can be implemented (63,89). investigating changes in neuromuscu-
tioners are often taught to use Recent research (89) has highlighted lar function have shown that with each
predictive tables to prescribe resistance the ability of velocity loss thresholds incremental increase in velocity loss
training loads and repetitions to maintain velocity and power outputs (e.g., 10, 20, and 30% velocity loss),
(12,35,80). This is despite the extremely when resistance training (Figure 5). linear reductions in function occur
large variance in the number of repeti- Furthermore, this work has demon- (88). This is supported by earlier work
tions that can be completed with a given strated how these thresholds can by Sanchez-Medina and González-
percentage of maximum (19). For exam- account for differences in individual Badillo (74) that assessed velocity and
ple, at 80% of 1RM, some individuals work capacity. Weakley et al. (89) estimated proximity to concentric fail-
can complete twice as many repetitions showed that when using velocity loss ure. Furthermore, near identical trends
as others (e.g., 8 vs. 16 repetitions) (72). thresholds, changes in mean barbell in perceived effort and metabolic re-
Thus, when prescribing 3 sets of 8 rep- velocity between athletes are possibly sponses also exist (i.e., greater exertion
etitions at 80% of 1RM, some athletes to likely trivial across 5 sets of the back and metabolic responses in line with
will be working to concentric failure, squat. This is in direct contrast to tra- greater increases in velocity loss) (88).
while others will complete these sets ditional prescription methods that These responses have been found to be
with relative ease. This heterogeneity cause very large reductions in velocity consistent within and between athletes
is likely due to a range of factors includ- as exercise goes on (85,94). These dif- and demonstrate exceptional levels
ing training history, gender, absolute ferences in the maintenance of kinetic of reliability within athletes across
strength levels, and recent training and kinematic outputs are due to the moderate- to long-term training peri-
exposure (19,42,72). Consequently, to unique “flexible-repetition” schemes ods (88).
Figure 5. Analysis of changes a powerlifter’s mean concentric velocity from 100-kg warm-up sets of the barbell back squat
throughout a 7-week training phase (raw data are showing in Figure 3). Changes are derived from baseline performance
established during a priori maintenance phase. CI 5 confidence interval; SGPV 5 second-generation p-value.
9
PROGRAMMING WITH VELOCITY- is vital for designing effective training term power-oriented resistance training
BASED TRAINING programs. Several studies have sug- program (64). Therefore, for accurate
Although the ability to have greater gested that the velocity associated with prescription of relative loads, it is
control over training outcomes is an a given percentage of 1RM is consistent advised to periodically assess the L-V
exciting prospect for the strength and across training sessions (3,8,18,24). relationship. Considering this, between
conditioning practitioner, understand- However, it has been shown that the athletes and training sessions, relative
ing the varying methods of program- velocity at a given %1RM may shift losses in exercise velocity cause consis-
ming that are available through VBT due to fatigue (86) or after a short- tent internal and external responses at
AU12 Figure 6. (A) The individual and mean group velocity (SD represented by the shaded area) when training with a 20% velocity loss
threshold across 3 sets of the back squat. Data from Weakley et al. (89). (B) The individual and mean group velocity (SD
represented by the shaded area) when training with 3 sets of the back squat with a set repetition scheme (i.e., 10
repetitions for all participants). Unpublished data from Weakley et al. (95). (C) The mean (6SD) velocity from graphs A and
B. Note the maintenance of velocity in the velocity-based training condition compared with the linear loss of velocity in
the percentage condition.

a given relative intensity (88,89). Conse- improved individualization and control the relative load prescribed by the
quently, previously well-established of training and subsequent responses strength coach may not match the rel-
training methods and their periodiza- can occur (21,89). ative load that is completed during
tion models can still be implemented. Due to changes in strength across the training. For example, a maximal
However, by using velocity to monitor training cycle, one issue with strength test from 4 weeks earlier will
and guide exercise prescription, percentage-based prescription is that not enable accurate prescription of load.
Table 5
Commonly used velocity-based training methods
Method (reference) Load Sets Repetitions Load

Set average velocity (9) The external load is prescribed from the athlete’s LVP. A set and Prescribed Prescribed Flexible
repetition scheme is prescribed. At the completion of the set,
the average set velocity is required to be within 0.06 m$s21
of initial prescribed velocity.
If average set velocity 60.06 m$s21, external load is
adjusted by 4–5% of 1RM.
Set average velocity + The external load is prescribed from an LVP. A number of Prescribed Flexible Flexible
VL thresholds (9,21) sets are prescribed with a velocity loss threshold used to
guide when set termination occurs (e.g., 20% velocity
loss). At the completion of the set, the average set
velocity is required to be within a required velocity zone
(e.g., 0.74–0.88 m$s21 during the back squat).
If average set velocity is not within this zone, the external
load can be manipulated.
Targeted velocity The athlete is prescribed a starting velocity (e.g., 0.70 m$s21) Prescribed Flexible Flexible
+ VL thresholds with the external load being altered to meet this velocity
(62,63,88,89) or velocity range (e.g., 0.70–0.75 m$s21) with the external
load being altered to meet this targeted velocity. A
velocity loss threshold (e.g., 10%) is used to guide set
termination.
During subsequent sets, if initial repetition velocity is
greater than 60.06 m$s21 of targeted velocity, an
additional 30-s recovery is provided. If the following
repetition’s velocity remains outside this range, external
load is adjusted by 4–5% of 1RM.
Fixed set + velocity loss The external load is prescribed from the athlete’s LVP. A Prescribed Flexible Prescribed
threshold (9) velocity loss threshold (e.g., 10%) is supplied with the
athlete terminating the set when velocity drops below
the velocity threshold.
Fixed total repetition + Before the session, a total number of repetitions are Flexible Prescribed Prescribed
flexible set + velocity prescribed (e.g., 25 repetitions). A load is prescribed from
loss threshold (9) the LVP, and a velocity loss threshold is used to guide set
termination. Athletes are allowed as many sets as they
require to complete the prescribed number of repetitions.
Fixed set + velocity Load is prescribed from LVP or targeted velocity, and Prescribed Flexible Prescribed
threshold + a velocity loss threshold is prescribed (e.g., 10%). In
repetition cap (9) addition, an upper limit of repetitions that can be
completed is prescribed (e.g., 5 repetitions). Athletes
exercise using the prescribed load until repetition velocity
decreases below velocity loss threshold or the repetition
limit is reached.
1RM 5 one repetition maximum; Flexible 5 an unknown amount that is often dictated by athlete fatigue/readiness (e.g., the athlete will
complete repetitions until barbell velocity drops below a certain threshold); LVP 5 load-velocity profile; Prescribed 5 dictated before the session
or after set (e.g., 5 sets).
11
Figure 7. Acute and chronic responses to training with smaller or larger velocity loss thresholds. MHC 5 myosin heavy chain.
Adapted from (62,63,88,89).
As a result, external loads that are sup- long-term planning. Furthermore, or “fixed” set and repetition schemes.
plied by practitioners are often too light within-session alterations in the external Traditional programming methods
or heavy. Established VBT methods can load can be made by the athlete or provide rigid programming (i.e., a num-
account for these fluctuations by moni- coach by simply referring to the MV of ber of sets and repetitions are pre-
toring velocity during the warm-up and the previous set (21) or the first repeti- scribed), but VBT can mitigate the
training session (89). Two of the most tion of the subsequent set (88,89) to differences in athletes and their physi-
common methods use either (I) a tar- ensure appropriate loading is occurring ological characteristics (89). For exam-
geted training velocity (e.g., an athlete during training. Alternatively, this infor- ple, a fixed number of sets may be
finds an external load within a given mation can be used to guide the termi- applied (e.g., 5 sets) with a flexible rep-
range that is being targeted that day nation of a training session (e.g., if an etition scheme (e.g., athletes exercise
[e.g., 0.70 6 0.05 m$s21]) (89) or (II) athlete consistently cannot meet until a 20% velocity loss has occurred)
a load (as a percentage of 1RM) that required velocities at a given load this (89). Alternatively, a fixed number of
meets a velocity from a previously estab- may indicate fatigue). repetitions could be prescribed (e.g.,
lished L-V profile (21). Both these One unique aspect of programming 25 repetitions) with a flexible number
methods enable reliable and accurate with VBT is that it allows for “flexible” of sets (e.g., each set is terminated
Figure 8. An example of a 6-week daily undulating mesocycle with athletes completing a strength endurance, strength, and power
sessions each week. The bullet point within each connected line signifies the average starting velocity from a given
session (e.g., strength session 1 5 0.54 m$s21). The dotted line indicates the stopping velocity (strength session 1 5 0.43
m$s21). Note the altering starting velocity and changes in velocity loss thresholds. VL 5 velocity loss.

Figure 9. Ten-week block periodization approach to programming the back-squat exercise. The bullet point within each connected
line signifies the average starting mean concentric velocity from a given week (e.g., week 1 5 0.64 m$s21). The dotted
line indicates the average stopping velocity (e.g., week 1 5 0.45 m$s21). Note that the velocity loss threshold reduces
across each mesocycle, while intensity increases. VL 5 velocity loss.
Table 6
Example of how velocity-based training for the back-squat exercise can be applied during a training week with one
match
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
1-Match
training wk
Velocity loss Rest 30% velocity loss Rest 20% velocity loss 10% velocity loss Rest Match
threshold day
Intensitya Rest ;0.70 m$s21/;65% Rest ;0.55m$s21/;82% ;1.00–0.60 Rest Match
(;m$s21/ 1RM 1RM m$s21/;30– day
% 1RM) 75% 1RM
Volume Rest ;9 repetitions per set Rest ;4–5 repetitions per ;2–6 repetitions Rest Match
set day
Internal Rest [[[ Metabolic Rest [[ Metabolic response [ Metabolic Rest Match
response response & and perception of response day
perception of effort effort [ 4 perception
of effort
Fatigue Rest [[ Perceived soreness Rest [ Perceived soreness 4Y Perceived Rest Match
response YY Neuromuscular 4Y Neuromuscular soreness day
function function [4
Neuromuscular
function
Velocity loss thresholds, initial intensity, approximate number of repetitions that will be completed, and estimated internal (during training) and
fatigue responses (24 h following training) are supplied are supplied to assist the practitioner. Information adapted from (6,8,9,88,89).
a
Initial velocity (mean concentric velocity) and relative percentage of 1RM may show slight deviations between athletes.
[[[ 5 large increase; [[ 5 moderate increase; [ 5 small increase; 4 5 trivial change; 4Y 5 trivial to small decrease; YY 5 moderate decrease;
1RM 5 one repetition maximum.
13
Table 7
Example of how velocity-based training for the back-squat exercise can be applied during a training week with 2 matches

2-Match training wk
Velocity loss Rest 10% velocity loss Rest Match day 10% velocity loss Rest Match
threshold day
Intensitya Rest ;0.55m$s21/;82% 1RM Rest Match day ;0.70m$s21/;65% 1RM Rest Match
(;m$s21/% 1RM) day
Volume Rest ;2–3 repetitions Rest Match day ;5 repetitions Rest Match
day
Internal response Rest 4 Metabolic response Rest Match day [ Metabolic response Rest Match
[ 4 perception of effort [ 4 perception of effort day
Fatigue response Rest 4Y Perceived soreness Rest Match day 4Y Perceived soreness Rest Match
[ 4 Neuromuscular [ 4 Neuromuscular day
function function
fatigue responses (24 h after training) are supplied to assist the practitioner. Information adapted from (6,8,9,88,89).
a
[ 5 small increase; [ 4 5 trivial to small increase; 4 trivial change; 4Y 5 trivial to small decrease; 1RM 5 one repetition maximum.
when velocity is reduced by 20%, with targeted. For example, block periodiza- greater control and prescription (Fig- F7 F9
athletes implementing as many sets as tion models that use phase potentia- ures 7–9).
necessary to complete the 25 repetition and greater volumes before
tions) (9). With identification of appro- heavier loads and lower volumes can PRACTICAL APPLICATIONS FOR
priate velocity loss cutoffs and their be applied and still follow traditional THE STRENGTH COACH
subsequent fatigue responses, these concepts (17,57). In a block periodized Maximizing performance through
flexible programming methods can model that uses VBT, initial phases physical training is the primary goal of
account for differing rates of fatigue, that aim to promote changes in all strength and conditioning professio-
between-athlete heterogeneity, and strength endurance and improvements nals. Therefore, applying VBT methods
daily readiness (89). This is shown in efficaciously is of great importance. It is
in body composition may use 30%
recent research (89), with flexible pro- acknowledged that individualization
velocity loss thresholds. This could
gramming enabling high levels of con- and greater homogeneity of fatigue re-
be followed by a strength mesocycle
sistency of both velocity and power sponses can occur when VBT is appro-
that allows for greater loads (i.e., lower
outputs between and within athletes priately applied (88,89). However,
when compared with regimented set starting velocities) and a smaller veloc-
strategic implementation can enhance
and repetition schemes based off a per- ity loss threshold (e.g., 20%) that causes
athlete buy-in and improve outcomes.
centage of an athlete’s previous maxi- less peripheral fatigue (63,89). Finally,
Below are practical suggestions that can
T5 mum (19,95). Table 5 outlines some of this could be followed by a strength- assist in the integration of VBT into the
the most commonly applied methods power or tapering mesocycle which training program.
of prescribing sets and repetitions uses a range of initial starting velocities
It has previously been recognized that
using VBT. with a very small velocity loss thresh-
providing feedback to athletes as they
Owing to the ability to accurately pre- old (e.g., 10%). These smaller thresh-
train can enhance velocity and power
scribe training load and volumes, it is olds have been shown to minimize
outputs by up to 10% (92,93,96). Fur-
also feasible to implement VBT in tra- fatigue while also ensuring greater thermore, because of the naturally
ditional programming models. Accu- power outputs during training (89). competitive nature of athletes, by al-
rate load prescription and velocity These concepts can be applied across lowing individuals of similar ability or
loss thresholds (e.g., 10% vs. 30%) that a range of different programming mod- position to train together and observe
induce a desired amount of fatigue can els (e.g., linear, daily/weekly undulat- each other’s kinematic outputs, greater
ensure that specific physical and phys- ing, conjugated) and can assist coaches competition may occur. However, the
iological characteristics can be in applying traditional approaches with intended purpose of the exercise must

Saturday
also be considered, as the feedback
Velocity loss thresholds, initial intensity, approximate number of repetitions that will be completed, and estimated internal (during training) and fatigue responses (24 h following training)
[[[ 5 large increase; [[ 5 moderate increase; [ 5 small increase. 4 5 trivial change; 4Y 5 trivial to small decrease; YY 5 moderate decrease; YYY 5 large decrease; 1RM 5 one
provided may cause an athlete to sac-
Match
Match
Match
Match
Match
day
day
day
day
day
rifice technique for greater velocities.
Although a great amount of publicity
has been given to VBT in recent years,
Friday
this has also led to practitioners occa-

Rest
Rest
Rest
Rest
Rest
sionally attempting to maximize veloc-
ities on exercises that are traditionally
4Y Neuromuscular function
performed for stability and range of
motion development, such as an over-
;0.70 m$s21/;65% 1RM
[[ Metabolic response &

head squat. When these movements
;7 repetitions per-set
Example of how velocity-based training for the back-squat exercise can be applied during preseason
perception of effort
[ Perceived soreness
Thursday
are performed quickly, they often lose

20% velocity loss
their intended purpose and benefits.

Consequently, feedback is suggested
to be best applied during exercises with
the greatest force and power outputs
(e.g., Olympic-style lifts, jumps, squats,
and bench press) (1,50,92,93,96).
As athletes participate in much more
Wednesday
than simply strength training, the man-
agement of fatigue is of great importance
Rest
Rest
Rest
Rest
Rest
for the strength coach. With relative

velocity loss thresholds, one can manage
the accrual of fatigue and cause more
YY Neuromuscular function
homogenous responses between ath-

[[[ Metabolic response &
letes. It is advised that during the “off-

;0.70 m$s21/65% 1RM
[[ Perceived soreness
Table 8
season” or general preparatory phase,

Tuesday
that greater velocity loss thresholds are

30% velocity loss
implemented as this period tends to

enable frequent strength training and
residual neuromuscular fatigue is unlikely
to have detrimental effects. Therefore,
are supplied to assist the practitioner. Information adapted from (6,8,9,88,89).
20–40% velocity loss thresholds may

be effective in these periods to elicit
greater adaptations in conditioning, lean
YYY Neuromuscular function
[[[ Metabolic response &
body mass, and muscular endurance

;0.60 m$s21/;80% 1RM
(63). Alternatively, in-season, smaller

[[ Perceived soreness
velocity loss thresholds (,20%) may

Monday
30% velocity loss
be of benefit in reducing fatigue and

ensuring training does not cause substan-
tial reductions in performance (88,89).
These concepts can also be applied
within an athlete’s training mesocycle
(refer to Tables 6–9) with previous T6 T9
research (88,89) implying that greater
Sunday
velocity losses (e.g., 30%) be applied at

Rest
Rest
Rest
Internal response Rest
Fatigue response Rest
the start of the week (e.g., match day

[MD] 25), with reductions occurring
as game day draws closer (e.g., 20% at
repetition maximum.
Preseason training
MD 23 and 10% at MD 22).

(;m$s21/%
Velocity loss
threshold
Finally, the ability to objectively dictate

Intensitya
Volume
1RM)
load can be of great use for the practi-

tioner (56). Regardless of the method of
wk
implementation, the ability to autoregu-

a
late loads based off velocity can support
15 Strength and Conditioning Journal | www.nsca-scj.com
Table 9
Example of how velocity-based training for the back-squat exercise can be applied during a tapering wk

Deload training
wk
Velocity loss Rest 10% velocity loss Rest Rest 10% velocity loss Rest Match
threshold day
Intensitya Rest ;0.50 m$s21/85% 1RM Rest Rest ;1.00–0.60 m$s21/ Rest Match
(;m$s21/% 30–75% 1RM day
1RM)
Volume Rest ;2–3 repetitions per-set Rest Rest ;2–6 repetitions Rest Match
day
Internal Rest [ Metabolic response & Rest Rest [ Metabolic Rest Match
response perception of effort response day
[ 4 perception of
effort
Fatigue Rest 4Y Perceived soreness Rest Rest 4Y Perceived Rest Match
response [ 4 Neuromuscular soreness day
function [4
Neuromuscular
function
fatigue responses (24 h following training) are supplied to assist the practitioner. Adapted from (6,8,9,88,89).
a
[ 5 small increase; [ 4 5 trivial to small increase; 4 Trivial change; 4Y 5 trivial to small decrease; 1RM 5 one repetition maximum.
the management of not only acute- sessions. This can enable practitioners congested training or match play. For
fatigue responses (e.g., between sets) to be confident in their exercise pre- example, practitioners are commonly
but also the accrual of fatigue across scription, even during periods of faced with the issue of athletes coming
straight off the training field and into the
weight room. This often means that the
athlete is fatigued and that the loads
prescribed before the training session
are no longer valid. However, VBT does
not face these issues as athletes are pre-
scribed a velocity range rather than
a specific external load. In addition,
because of the many outside stressors
that can impact an athlete (e.g., aca-
demic stress) (54), VBT may support F10
load management (Figure 10). AU7
CONCLUSIONS
VBT uses exercise velocity to inform or
Figure 10. An example of a linear periodization approach to programming the back
enhance training practice. It can be im-
squat with a 20% velocity loss threshold applied across a 10-week training
macrocycle. The bullet point within each connected line signifies the plemented as a tool that works alongside
starting velocity from a given week (e.g., week 1 5 0.82 m$s21). The dotted traditional percentage-based methods
line indicates the set termination velocity (e.g., week 1 5 0.66 m$s21). Note (e.g., the provision of feedback), or it
that the velocity loss threshold reduces across the macrocycle (emphasized can be used to autoregulate the training
by the arrows) despite the threshold not changing. This allows for increased volume and intensity for each athlete.
intensity but reduced volumes across time. From this review, it is advised that:

An important consideration for the Practitioners should consider regu-
Harry Banyard
practitioner is the validity of the larly monitoring velocity (this could
is a lecturer at the
device that is used to monitor veloc- be performed at the start of a training
Swinburne Uni-
ity. Current evidence suggests that session) to help objectively monitor
versity of
linear position transducers should changes in athlete fitness/fatigue. By
Technology.
be used due to their greater accuracy. monitoring the typical day-to-day
Feedback of performance is provided fluctuations in velocity (i.e., the SE)
either visually or verbally to athletes and applying this to a meaningful
as they train. This feedback should threshold (e.g., change in strength),
be at frequent intervals (e.g., after practitioners can gain regular objec-
each repetition) and used during tive insight into the effects of their
high force and power exercises (i.e., training program.
Shaun
primary, multijoint exercises). Velocity loss thresholds can account
McLaren is
For testing performance during bal- for between-athlete differences in
a sport scientist at
listic exercises with loads that are muscular endurance and also miti-
England Rugby
#70% of 1RM, PV should be used. gate heterogeneity in short-term
League and
Alternatively, PV or MV could be fatigue responses. By altering the
research assistant
used for testing performance .70%. velocity loss threshold, internal and
at Leeds Beckett
For the prediction of 1RM ability, subsequent fatigue responses
University.
MV should be used. This is due to increase or decrease.
smaller differences between different Prescription of training using VBT
testing devices, greater linearity of can occur in many ways. These
the L-V relationship, and smaller methods can fit within traditional
Tannath Scott
between-athlete variation in the periodization models and can be
is a postdoctoral
velocity that 1RM occurs. used to guide exercise prescription
research fellow at
The “2-point method” has been with greater confidence.
the University of
shown to be a valid method of cal- New England
Conflicts of Interest and Source of Funding:
culating the 1RM from the L-V pro- and New South
The authors report no conflicts of interest
file during upper-body exercises. Wales Rugby
and no source of funding. AU3
This involves (I) identifying the League.
exercise-specific V1RM, (II) record-
ing the MV against a light (z45% Jonathon
1RM) and a heavy load (z85% Weakley is a lec-
1RM), and (III) modeling the indi- turer at Austra- Amador
vidual L-V relationship and deter- lian Catholic Garcia-Ramos
mining the 1RM as the load University, is a professor at
associated with the V1RM. Coaches a research associ- the University of
should be aware that the accuracy of ate at Leeds Granada and
the 2-point method and other Beckett Univer- Universidad Ca-
velocity-based 1RM prediction sity, and Sport to´lica de la San-
methods is expected to be lower dur- Science consul- tı´sima
ing lower-body exercises. tant for the Queensland Reds. Concepcio´n. AU4
By quantifying an athlete’s L-V pro-
file and using an accurate velocity
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Velocity-Based Training From Theory To Application

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Velocity-Based Training:

ABSTRACT to an individual’s maximal ability (e.g., integration of VBT lies on a continuum

A ing to develop strength, power,

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Exercise Study Sample 1RM MV (mean 6 SD) V1RM

1RM 5 one repetition maximum; MV 5 mean velocity; V1RM 5 velocity at 1RM.

1RM 5 one repetition maximum.

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Table 4 expert coach opinion or existing

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Method (reference) Load Sets Repetitions Load

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Sunday Monday Tuesday Wednesday Thursday Friday Saturday

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this has also led to practitioners occa-

[[ Metabolic response &

are performed quickly, they often lose

their intended purpose and benefits.

for the strength coach. With relative

homogenous responses between ath-

letes. It is advised that during the “off-

season” or general preparatory phase,

that greater velocity loss thresholds are

implemented as this period tends to

20–40% velocity loss thresholds may

body mass, and muscular endurance

(63). Alternatively, in-season, smaller

velocity loss thresholds (,20%) may

30% velocity loss

be of benefit in reducing fatigue and

velocity losses (e.g., 30%) be applied at

Internal response Rest

Fatigue response Rest

the start of the week (e.g., match day

MD 23 and 10% at MD 22).

Finally, the ability to objectively dictate

load can be of great use for the practi-

implementation, the ability to autoregu-

late loads based off velocity can support

15 Strength and Conditioning Journal | www.nsca-scj.com

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

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